Organizers

Cancer and tumor-induced angiogenesis has a natural place in the Special Year on Developmental Biology as cancer is often thought of as a result of a faulty development process. Experimental and clinical oncology forms a massive literature aimed at understanding and treating cancer. Despite the enormity of the data available, clinical oncologists and tumor biologists proceed without a comprehensive theoretical model to help guide the organization and understanding of such data. To quote a recent Nature article on the topic:

Heeding lessons from the physical sciences, one might expect to find oncology aggressively, almost desperately, pursuing quantitative methods to consolidate its vast body of data and integrate the rapidly accumulating new information. In fact, quite the contrary situation exists. Mathematical models are typically denounced as "too simplistic" for complex tumour-related phenomena (ignoring, of course, the fact that similar simplifying assumptions are required in most experimental designs). Articles in cancer journals rarely feature equations. Clinical oncologists and those who are interested in the mathematical modelling of cancer seldom share the same conference platforms. -- Nature 421, 321 (2003).

Naturally, successful modeling approaches to cancer requires scientists willing to communicate and interact extensively across disciplinary boundaries. This workshop aims to do exactly this by having truly interdisciplinary scientists as well as giving a shared platform for both experienced modellers and state-of-the art experimentalists and clinician-scientists discussing their work covering every level of tumor growth.

Each day of the workshop, will consist of 3 primary speakers (1-hour lectures each) that will include an experimentalist laying out the biological problem, a mathematical modeler describing modeling approaches and a imaging specialist describing the type of data (typically imaging) available for model validation and development. Additionally, other attendees will be invited to present posters at the poster session. An expert panel will comprise of leading modelers and experimentalists to discuss current problems in the efficient translation of mathematical modeling techniques to the laboratory and the clinic.

Significant time will be available during the meeting for discussions of current and future problems in the cancer and tumor-induced angiogenesis area.

Accepted Speakers

Alexander (Sandy) Anderson

Division of Mathematics, University of Dundee

Gustavo Ayala

Departments of Pathology, Urology, and Molecular and Cellular Biology, Baylor University

Kristin Swanson - Current state-of-the-art in mathematical modeling in cancer: Cellular to Organ to Patient

N/A

02:00 PM 03:00 PM

Alexander (Sandy) Anderson - Current state-of-the-art in mathematical modeling in cancer: Subcellular to Cellular to Organ

N/A

03:30 PM 04:30 PM

Robert Gatenby - Does cancer use "spite" as an evolutionary strategy? Warbug revisited

It is generally accepted that carcinogenesis is formally analogous to Darwinian evolution as environmental selection forces act on new phenotypes that are continuously generated through accumulating genetic mutations and epigenetic changes. Those intracellular phenotypes that yield a proliferative advantage are rewarded by clonal expansion and persistence in the population. This process yields progressive fitter populations until a fitness maximum is reached and an invasive cancer emerges.

Since the pioneering studies of Warburg, it has been consistently demonstrated that invasive cancers maintain a high rate of anaerobic glucose metabolism even in the presence of oxygen. Widespread application clinical of FDG-PET imaging has demonstrated the vast majority (perhaps all) clinical primary and metastatic cancers exhibit significantly increased glucose flux as a result of glycolytic metabolism.

Within the context of somatic evolution, selective use of glycolytic pathways even in the presence of oxygen seems paradoxic. Anaerobic metabolism of glucose is inefficient (yielding 2 ATP /glucose vs. 36-38 ATP/glucose for aerobic metabolism) and produces acid as a byproduct. It would seem that, in general, Darwinian principles would favor more efficient and less potentially toxic metabolism.

We investigate development of aerobic glycolysis using quantitative methods from evolutionary game theory. The models demonstrate a previously unknown era during carcinogenesis in which cellular evolution is driven by limited substrate availability. Specifically we find that adaptation to cyclical hypoxia within premalignant lesions will result in constitutive upregulation of glycolysis. The reduction in extracellular pH caused by upregulation of glycolysis then requires additional cellular evolution to overcome acid-induced toxicity. We find this evolutionary sequence is critical to formation of an invasive cancer because it produces a phenotype that alters its environment (through increased acid production) in a way that is toxic to its competitors but less harmful to itself.

This suggests that cancer cells use an evolutionary strategy previously described as "spite." That is, they reduce their own fitness through aerobic glycolysis but, by doing so, reduce the fitness of their competitors even more.

Experimental support for the acid-mediated tumor invasion hypothesis will be presented along with new treatment strategies that emerge from the model.

To effectively monitor protein phosphorylation events governing signaling cascades, we have developed a mass spectrometry-based methodology enabling the simultaneous quantification of tyrosine phosphorylation of specific residues on dozens of key proteins at multiple time points under a variety of perturbations. We have recently applied this technique to identify key signaling nodes regulating tamoxifen resistance in breast cancer as well as proliferation in glioblastoma. Inhibition of these nodes with small molecule kinase inhibitors results in reversion of resistance or decrease in proliferation in each system. Overall, we have now demonstrated that the combination of mass spectrometry-based analysis of protein phosphorylation with phenotypic measurements and computational modeling yields novel insights into the regulation of cellular signaling on a network scale.

Recent cancer therapies have targeted tumor blood vessels with inconsistent results. Some treatments show promise while others fail, underscoring a frustrating lack of understanding of the mechanisms that control blood vessel formation, destruction and function. A major difficulty lies in the fact that the mechanisms of vessel formation and remodeling operate at multiple scales, each with its own set of controls, and each critical to the overall function of the blood vessel network. Most importantly, "rare" events occurring at the single cell level can dominate overall vessel network function, and therefore, tumor growth. Analytical approaches--both experimental and computational-- that span the size scale from single cells to the bulk tumor should incorporate the relevant parameters critical for understanding tumor growth. Experimentally, intravital microscopy allows determination of single-vessel hematocrit, blood velocity, permeability as well as vessel and network morphology over time. Mathematical models of blood flow, vessel growth & remodeling, and tumor growth and invasion span the size scale from cells to tissue to elucidate the cellular events that influence tissue-scale physiology. These tools will provide a framework for studying the effects of anti-tumor therapies and improving their efficacy.

11:00 AM 12:00 PM

Muhammad Zaman - Modeling Tumor Cell Invasion

N/A

02:00 PM 03:00 PM

David Morse - Imaging the Hallmarks of Cancer in the Tumor Microenvironment

It was proposed by Hanahan & Weinberg (Cell 2000, 100: 57-70) that most if not all cancers acquire the same set of universal phenotypic traits, or "Hallmarks," through a variety of mechanistic strategies. Namely, the ability to evade programmed cell death, self-sufficiency in growth signals, insensitivity to anti-growth signals, limitless replicative potential, sustained angiogenesis and tissue invasion and metastasis. More recently, Gatenby and Gillies (Nature Reviews Cancer 2008, 8: 56-61) have proposed a microenvironmental model of carcinogenesis that includes the glycolytic phenotype (Warburg effect) and adaptation to growth in the presence of chronic acidosis as an additional "Hallmark." A number of ex vivo and in vivo imaging strategies have been developed which interrogate the morphological, physiological and metabolic phenotype of the evolving tumor microenvironment. Diffusion-weighted magnetic resonance imaging (DW-MRI) and magnetic resonance spectroscopic imaging (MRSI) of choline metabolites can both be used to observe cell proliferation and death. Positron emission tomography (PET) is used to image hypoxia and glucose uptake by uptake of 18F-fluoromisonidazole (FMISO) or 18F-2-fluoro-2-deoxy-D-glucose (FDG) respectively. FMISO accumulates in hypoxic cells but there is no accumulation at pO2 > 10mmHg. FDG is an analog of glucose. Tumor pH is measured by MRSI or fluorescence imaging of pH sensitive agents, e.g. 3-aminopropylphosphonate and SNARF-1 fluorescent dye. Metastasis can be observed and quantified by optical imaging of metastases originating from cells expressing fluorescent protein or luciferase. Hence, these imaging modalities can be used to study tumor phenotypic parameters that are related to the hallmarks of cancer.

Carl Panetta - An Introduction to Pharmacokinetic and Pharmacodynamic Modeling

Pharmacokinetics (PK) is the study of the disposition of drugs (absorption, distribution, metabolism, and elimination) in the body and pharmacodynamics (PD) is the study of the effects of the drugs on the body. Over the last several decades PK/PD modeling has evolved into a complete mathematical/statistical subfield in pharmaceutical research and is now involved in all aspects of drug development from in vitro to clinical studies. There are several reasons why PK/PD models are developed. First, they are used to describe data such as plasma concentrations of a drug and/or its metabolite (PK) or the effect of the drug on a target such as a cell or receptor (PD). This descriptive information can be used to determine if effective concentrations are being obtained to cause the desired effect without causing excessive toxicity. In addition, PK/PD models are used to predict drug concentrations and/or effects. For example the drug disposition for a multiple dosing regimen can be predicted given the data from just one dose. The PK/PD modeling process first involves model building which is as much of an art as a science. This is followed by model parameter estimation using methods such as weighted least squares, maximum likelihood estimation, or maximum a posteriori probability estimation (Bayesian estimation). This session will provide an introduction to the process of PK/PD modeling using examples from pediatric oncology.

Name

Email

Affiliation

Andasari, Vivi

vivi@maths.dundee.ac.uk

Division of Mathematics, University of Dundee

Anderson, Alexander (Sandy)

Yvette.Mieles@moffitt.org

Division of Mathematics, University of Dundee

Ayala, Gustavo

kj1@bcm.tmc.edu

Departments of Pathology, Urology, and Molecular and Cellular Biology, Baylor University

It is generally accepted that carcinogenesis is formally analogous to Darwinian evolution as environmental selection forces act on new phenotypes that are continuously generated through accumulating genetic mutations and epigenetic changes. Those intracellular phenotypes that yield a proliferative advantage are rewarded by clonal expansion and persistence in the population. This process yields progressive fitter populations until a fitness maximum is reached and an invasive cancer emerges.

Since the pioneering studies of Warburg, it has been consistently demonstrated that invasive cancers maintain a high rate of anaerobic glucose metabolism even in the presence of oxygen. Widespread application clinical of FDG-PET imaging has demonstrated the vast majority (perhaps all) clinical primary and metastatic cancers exhibit significantly increased glucose flux as a result of glycolytic metabolism.

Within the context of somatic evolution, selective use of glycolytic pathways even in the presence of oxygen seems paradoxic. Anaerobic metabolism of glucose is inefficient (yielding 2 ATP /glucose vs. 36-38 ATP/glucose for aerobic metabolism) and produces acid as a byproduct. It would seem that, in general, Darwinian principles would favor more efficient and less potentially toxic metabolism.

We investigate development of aerobic glycolysis using quantitative methods from evolutionary game theory. The models demonstrate a previously unknown era during carcinogenesis in which cellular evolution is driven by limited substrate availability. Specifically we find that adaptation to cyclical hypoxia within premalignant lesions will result in constitutive upregulation of glycolysis. The reduction in extracellular pH caused by upregulation of glycolysis then requires additional cellular evolution to overcome acid-induced toxicity. We find this evolutionary sequence is critical to formation of an invasive cancer because it produces a phenotype that alters its environment (through increased acid production) in a way that is toxic to its competitors but less harmful to itself.

This suggests that cancer cells use an evolutionary strategy previously described as "spite." That is, they reduce their own fitness through aerobic glycolysis but, by doing so, reduce the fitness of their competitors even more.

Experimental support for the acid-mediated tumor invasion hypothesis will be presented along with new treatment strategies that emerge from the model.

It was proposed by Hanahan & Weinberg (Cell 2000, 100: 57-70) that most if not all cancers acquire the same set of universal phenotypic traits, or "Hallmarks," through a variety of mechanistic strategies. Namely, the ability to evade programmed cell death, self-sufficiency in growth signals, insensitivity to anti-growth signals, limitless replicative potential, sustained angiogenesis and tissue invasion and metastasis. More recently, Gatenby and Gillies (Nature Reviews Cancer 2008, 8: 56-61) have proposed a microenvironmental model of carcinogenesis that includes the glycolytic phenotype (Warburg effect) and adaptation to growth in the presence of chronic acidosis as an additional "Hallmark." A number of ex vivo and in vivo imaging strategies have been developed which interrogate the morphological, physiological and metabolic phenotype of the evolving tumor microenvironment. Diffusion-weighted magnetic resonance imaging (DW-MRI) and magnetic resonance spectroscopic imaging (MRSI) of choline metabolites can both be used to observe cell proliferation and death. Positron emission tomography (PET) is used to image hypoxia and glucose uptake by uptake of 18F-fluoromisonidazole (FMISO) or 18F-2-fluoro-2-deoxy-D-glucose (FDG) respectively. FMISO accumulates in hypoxic cells but there is no accumulation at pO2 > 10mmHg. FDG is an analog of glucose. Tumor pH is measured by MRSI or fluorescence imaging of pH sensitive agents, e.g. 3-aminopropylphosphonate and SNARF-1 fluorescent dye. Metastasis can be observed and quantified by optical imaging of metastases originating from cells expressing fluorescent protein or luciferase. Hence, these imaging modalities can be used to study tumor phenotypic parameters that are related to the hallmarks of cancer.

Recent cancer therapies have targeted tumor blood vessels with inconsistent results. Some treatments show promise while others fail, underscoring a frustrating lack of understanding of the mechanisms that control blood vessel formation, destruction and function. A major difficulty lies in the fact that the mechanisms of vessel formation and remodeling operate at multiple scales, each with its own set of controls, and each critical to the overall function of the blood vessel network. Most importantly, "rare" events occurring at the single cell level can dominate overall vessel network function, and therefore, tumor growth. Analytical approaches--both experimental and computational-- that span the size scale from single cells to the bulk tumor should incorporate the relevant parameters critical for understanding tumor growth. Experimentally, intravital microscopy allows determination of single-vessel hematocrit, blood velocity, permeability as well as vessel and network morphology over time. Mathematical models of blood flow, vessel growth & remodeling, and tumor growth and invasion span the size scale from cells to tissue to elucidate the cellular events that influence tissue-scale physiology. These tools will provide a framework for studying the effects of anti-tumor therapies and improving their efficacy.

Pharmacokinetics (PK) is the study of the disposition of drugs (absorption, distribution, metabolism, and elimination) in the body and pharmacodynamics (PD) is the study of the effects of the drugs on the body. Over the last several decades PK/PD modeling has evolved into a complete mathematical/statistical subfield in pharmaceutical research and is now involved in all aspects of drug development from in vitro to clinical studies. There are several reasons why PK/PD models are developed. First, they are used to describe data such as plasma concentrations of a drug and/or its metabolite (PK) or the effect of the drug on a target such as a cell or receptor (PD). This descriptive information can be used to determine if effective concentrations are being obtained to cause the desired effect without causing excessive toxicity. In addition, PK/PD models are used to predict drug concentrations and/or effects. For example the drug disposition for a multiple dosing regimen can be predicted given the data from just one dose. The PK/PD modeling process first involves model building which is as much of an art as a science. This is followed by model parameter estimation using methods such as weighted least squares, maximum likelihood estimation, or maximum a posteriori probability estimation (Bayesian estimation). This session will provide an introduction to the process of PK/PD modeling using examples from pediatric oncology.

To effectively monitor protein phosphorylation events governing signaling cascades, we have developed a mass spectrometry-based methodology enabling the simultaneous quantification of tyrosine phosphorylation of specific residues on dozens of key proteins at multiple time points under a variety of perturbations. We have recently applied this technique to identify key signaling nodes regulating tamoxifen resistance in breast cancer as well as proliferation in glioblastoma. Inhibition of these nodes with small molecule kinase inhibitors results in reversion of resistance or decrease in proliferation in each system. Overall, we have now demonstrated that the combination of mass spectrometry-based analysis of protein phosphorylation with phenotypic measurements and computational modeling yields novel insights into the regulation of cellular signaling on a network scale.

Modeling Tumor Cell Invasion

Muhammad Zaman (Department of Biomedical Engineering and Institute of Theoretical Chemistry, University of Texas)

The MBI receives major funding from the National Science Foundation Division of Mathematical Sciences and is supported by The Ohio State University.
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